The present invention pertains to fabrication of integrated circuits and more particularly to systems and methods for improving fabrication yields.
The fabrication of integrated circuits is an extremely complex process that may involve hundreds of individual operations. Basically, the process includes the diffusion of precisely predetermined amounts of dopant material into precisely predetermined areas of a silicon wafer to produce active devices such as transistors. This is typically done by forming a layer of silicon dioxide on the wafer, then utilizing a photomask and photoresist to define a pattern of areas into which diffusion is to occur through a silicon dioxide mask. Openings are then etched through the silicon dioxide layer to define the pattern of precisely sized and located openings through which diffusion will take place. After a predetermined number of such diffusion operations have been carried out to produce the desired number of transistors in the wafer, they are interconnected as required by interconnection lines. These interconnection lines, or interconnects as they are also known, are typically formed by deposition of an electrically conductive material which is defined into the desired interconnect pattern by a photomask, photoresist and etching process. A typical completed integrated circuit may have millions of transistors contained with a 0.1 inch by 0.1 inch silicon chip and interconnects of submicron dimensions.
In view of the device and interconnect densities required in present day integrated circuits, it is imperative that the manufacturing processes be carried out with utmost precision and in a way that minimizes defects. For reliable operation, the electrical characteristics of the circuits must be kept within carefully controlled limits, which implies a high degree of control over the myriad of operations and fabrication processes. For example, in the photoresist and photomask operations, the presence of contaminants such as dust, minute scratches and other imperfections in the patterns on the photomasks can produce defective patterns on the semiconductor wafers, resulting in defective integrated circuits. Further, defects can be introduced in the circuits during the diffusion operations themselves. Defective circuits may be identified both by visual inspection under high magnification and by electrical tests. Once defective integrated circuits have been identified, it is desired to take steps to decrease the number of defective integrated circuits produced in the manufacturing process, thus increasing the yield of the integrated circuits meeting specifications.
In the past, many of the defects which caused poor yield in integrated circuits were caused by particulate contaminants or other random sources. Increasingly, many of the defects seen in modern integrated circuit processes are not sourced from particulates or random contaminants, especially in the earlier stages of process development or yield ramping, but rather stem from very systematic sources. Examples of these systematic defect sources include printability problems from using aggressive lithography tools, poly stringers from poorly formed silicides, gate length variation from density driven and optical proximity effects.
In attempting to decrease the number of defective integrated circuits produced in the manufacturing process, thus increasing the yield, one is faced with the fact that any one or more of possibly several hundred processing steps may have caused a particular circuit to be defective. With such a large number of variables to work with, it can be extremely difficult to determine the exact cause or causes of the defect or defects in a particular circuit thereby making it extraordinarily difficult to identify and correct the yield detracting process operations. Detailed inspection of the completed integrated circuits may provide some indication of which process operation may have caused the circuits to be defective. However, inspection equipment often does not capture many of the systematic defect sources and/or the tools can be difficult to tune, optimize, or use effectively and reliably. Furthermore, inspection equipment, especially in recent technologies is often plagued with many false alarms or nuisance defects, as they are known, which serve to frustrate any attempts to reliably observe true defects or sources of defects.
It is typically discovered that, once a particular problem has been identified at final test after completion of the fabrication cycle, it can be confirmed that a problem in a particular process operation did exist at the time that operation was carried out, which could have been weeks or even months earlier. Thus the problem might be corrected well after the fact. At this time, different process operations may be causing problems. Thus, after the fact analysis of defective integrated circuits and identification of process operations causing these defective products is severely limited as a means for improving the overall yield of integrated circuits.
A number of attempts to predict yields instead of conducting unsatisfactory after the fact analysis have been made with varying degrees of success. Thus, there is a need for an improved system and method for integrated circuit product yield prediction.
A system and method for predicting yield of integrated circuits includes at least one type of characterization vehicle which incorporates at least one feature which is representative of at least one type of feature to be incorporated in the final integrated circuit product. The characterization vehicle is subjected to at least one of the process operations making up the fabrication cycle to be used in fabricating the integrated circuit product in order to produce a yield model. The yield model embodies a layout as defined by the characterization vehicle and preferably includes features which facilitate the gathering of electrical test data and testing of prototype sections at operating speeds. An extraction engine extracts predetermined layout attributes from a proposed product layout. Operating on the yield model, the extraction engine produces yield predictions as a function of layout attributes and broken down by layers or steps in the fabrication process. These yield predictions are then used to determine which areas in the fabrication process require the most improvement.